As a leader in the construction and building services industry, EllisDon is determined to minimize the impact of the carbon emissions generated by the construction process and the operational impacts of infrastructure around the globe.
We also know that our clients are adopting net zero and decarbonization for their facilities. Reaching those targets, however, can be costly and challenging. With EKO, we help our clients achieve their energy goals faster with the technology and data that already exists within their facilities. As we say, “You can’t be GREEN unless you’re SMART.™”
The EKO Sustainability module provides predictive optimization models to enhance energy efficiency. These models deliver accurate energy demand forecasting, efficient control of building assets and cost minimization, while maintaining occupant comfort. This module is composed of the following:
Sustainability
Energy Demand Prediction
EKO predicts energy demand based on variables, utilizing supervised machine learning models, including device usage patterns, ambient sensor data and external weather data in the near-term horizon.
Energy Consumption Optimization
EKO uses forecasted energy demand from its energy demand prediction process to explore heuristic and mathematical optimization methods to optimize energy consumption across units in a building. This allows operators to reduce energy use within their facilities, while also maintaining user comfort.
Energy Source Selection
EKO enables the strategic toggling among various energy sources to reduce peak demands and reduce reliance on carbon-based fuel supply. To accomplish this, EKO incorporates optimal energy source selection as part of the Energy Consumption Optimization solution, noted above.
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